Characterising Student Engagement Modes through Low-Level Activity Patterns
Research output: Contribution to book/Conference proceedings/Anthology/Report › Conference contribution › Contributed › peer-review
Contributors
Abstract
Existing approaches to characterise engagement in online learning focus on features of the interaction of students with the learning platform including the number of posts in forums, downloads of learning materials and time spent watching videos. However, little is known about what students actually do within the learning resources and whether these activities are indicators of learning outcomes. To bridge this gap, we associate low-level activity patterns with particular student engagement modes on a connectivist MOOC (cMOOC) that ran for four weeks and involved 224 students. Our findings indicate that our approach isolates meaningful interactive behavioural markers that are indicators of engagement, and are amenable to computation.
Details
Original language | English |
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Title of host publication | Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization |
Number of pages | 10 |
ISBN (electronic) | 9781450383660 |
Publication status | Published - 21 Jun 2021 |
Peer-reviewed | Yes |
External IDs
Scopus | 85109476066 |
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ORCID | /0000-0001-5096-8851/work/142240963 |